Proceedings Paper

Much literature on image registration has worked with purely geometric image deformation models. For such models, interpolation/resampling operations are often the computationally
intensive steps when iteratively minimizing the deformation cost
function. This article discusses some techniques for efficiently
implementing and accelerating these operations. To simplify presentation, we discuss our ideas in the context of 2D imaging. However, the concepts readily generalize to 3D. Our central technique is a table-lookup scheme that makes somewhat liberal use of
RAM, but should not strain the resources of modern processors if certain design parameters are appropriately selected. The technique works by pre-interpolating and tabulating the grid values of the reference image onto a finer grid along one of the axes of the image. The lookup table can be rapidly constructed using FFTs. Our results show that this technique reduces iterative computation by an order of magnitude. When a minimization algorithm employing coordinate block alternation is used, one can obtain still faster computation by storing certain intermediate quantities as state variables. We refer to this technique as state variable hold-over. When combined with table-lookup, state variable hold-over reduces CPU time by about a factor two, as compared to table-lookup alone.